Ultrasound and Infrared-Based Imaging Modalities for Diagnosis and Management of Cutaneous Diseases
Bibliographic record
Abstract
Non-invasive bedside imaging tools are becoming more prevalent for assessing cutaneous lesions. Ultrasound used at specific frequencies allows us to assess margins of lesions to minimize the extent of the biopsy that is performed and improve cosmetic outcomes. Vascularity, seen on Doppler ultrasound and contrast-enhanced ultrasound, and stiffness, assessed on tissue elastography, can help differentiate between benign and malignant lesions for clinicians to be more judicious in deciding whether to biopsy. Moreover, research has shown the efficacy in using ultrasound in monitoring flares of hidradenitis suppurativa, a disease affecting apocrine gland-rich areas of the body, for which the current gold standard involves examining and scoring inflammatory lesions with the naked eye. Infrared-based modalities have also been on the uptrend to aid in clinical decision-making regarding suspiciousness of lesions. Reflectance confocal microscopy has lateral resolution that is comparable to histopathology and it has been shown to be an appropriate adjunctive tool to dermoscopy, specifically when evaluating melanomas. Optical coherence tomography has utility in determining lesion thickness because of its depth penetration, and spectrophotometric intracutaneous analysis is becoming more popular as a tool that can be used by general practitioners to know when to refer to dermatology regarding worrisome pigmented lesions. Strides have been made to incorporate electrical impedance spectroscopy alongside dermoscopy in decision-making regarding excision, although the evidence for its use in the clincial setting remains inconclusive. This paper reviews the efficacy and drawbacks of these techniques in the field of dermatology and suggests future directions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".